Measurement of electrical bioimpedance enables to characterize a state of tissues/organs, to get diagnostic images, to find hemodynamical parameters, etc.
An excitation current is applied to the tissue under the study and a voltage response is measured. There are two different current paths through the tissue, the first one proceeds through the extracellular fluid and has a resistive character, and the other (intracellular) passes through the cell membranes and thus, has a capacitive character. The electrical bioimpedance Ż=V/Iexc can be expressed as a complex parameter:Ż=R+jX=Z·ejΦ,with a real part R and an imaginary (capacitive) part X, or a magnitude Z and a phase Φ.
Bioimpedance measurement has number of applications, including in cardiography, e.g., noninvasive plethysmography, multielectrode invasive estimation of the ventricular volume, intracardiac impedance based pacing control, and biomodulation measurements (see also FIGS. 1 to 3).
Engineering Background
As a rule, parameterization of different compartments of a tissue or an organ is required. Therefore, the impedance of tissues and organs is measured between electrodes having different location. The time domain variation of impedances can differ significantly at different sites. Also variations of impedance at distant low and high (ωL and (ωH) excitation frequencies can be quite different. The frequency dependence can be explained by Ż(ωL) and Ż(ωH) of the three element electrical equivalent.
Analog synchronous demodulation (SD) has been a preferred tool for electrical bioimpedance (EBI) measurement for many decades already, especially in portable, wearable and implantable medical devices. However, with advancements of microelectronics, a shift from analog signal processing towards digital has become more and more justified. Digital solutions allow reduction in size, reduce energy consumption, complexity and price. Also, digital techniques can enhance reliability trough redundancy in mission critical medical devices. Also, the flexibility of digital systems through their programmability will decide in favor of digital solutions.
According to typical digital solution, the response voltage is digitized in an analog-to-digital converter (ADC) into a uniformly sampled train of digital data, which is then processed numerically in a digital signal processing (DSP) unit, often using the Discrete Fourier Transform (DFT). However, transforming the time domain processes into frequency domain and applying then FFT for frequency domain extraction to different frequency components from the composite response signal, and applying the inverse FFT for getting back the time domain processes, is a complicated digital processing which requires powerful processors for performing it in real time and fulfilling the Nyquist criterion (sampling rate must be at least two to five time of the frequency of the signal component).
Required, therefore, is an approach that requires less computational power using undersampling (sampling rate lower than the Nyquist rate).
Using of sampling, which is synchronous to the known excitation waveform enables to use a simplified, but much faster signal processing than Fourier Transform is. When sampling the response signal uniformly with intervals τ=T/4 (see FIG. 4), where T is a period of the signal, the following simple mathematics is valid:
the direct current component DC can be determined asDC=(Re++Re−)/2 or DC=(Im++Im−)/2,
and the real Re and imaginary Im parts of the phasor Ż of complex impedance is determined asRe=(Re+−Re−)/2, and Im=(Im+−Im−)/2.
If the frequency of excitation signal is too high compared to the speed of analog to digital converter, or the power resources are limited, it is reasonable to use undersampling, keeping an exact synchronization between the excitation and sampling (see T. Dudykevych, E. Gersing, F. Thiel and G. Hellige, “Impedance Analyser Module for EIT and Spectroscopy Using Undersampling”, Physiological Measurement, No. 22, Institute of Physics Publ. Ltd, UK, pp. 19-24, 2001; U.S. provisional application 60/580,831 and PCT/EE2005/000008 to Min et al).
When examining body parts or organs (thorax, heart, myocardium, lungs etc), only a single frequency excitation cannot give sufficient information about the bio-object. At least the two-frequency measurement is necessary according to the simple two-element equivalent circuit. The measurements at several frequencies must be performed simultaneously to follow the dynamic behavior of the changing bio-object properly (see above patent applications to Min).
For example, a digital multichannel bioimpedance analyzer must perform simultaneous measurement of complex bioimpedances (between the electrodes put into the heart) at eight frequencies from 1 or 10 kHz up to 1 MHz. The sinusoidal excitation currents of these frequencies must be sent to (K=1, 2 or 4) excitation electrodes and the summary response voltages must be measured at (up to) four measurement electrodes. Every response is a sum of eight excitations modulated by slowly varying bioimpedances (which include heartbeat and breathing components) and a slowly varying offset (caused by bioelectrical activity of the heart).
Proposed, therefore, are algorithms to measure the electrical bioimpedance, using numerical synchronous detection.
One suggestion is to extend synchronous sampling to the multifrequency measurement. Several, only slightly different frequencies are used instead of a single frequency excitation when different impedances of the organ are measured simultaneously (FIG. 5) or a single impedance at different frequencies (FIG. 6). However, the non-uniform nature of the resulting sampling pattern should be noted in this case (FIGS. 7 and 8). For example, when considering impedance cardiography (ICG) or similar applications, responses from several points are required to receive simultaneously together with the need to simultaneous multipoint excitation. It can be achieved using several slightly different excitation frequencies. Of course, this frequency differences must be small enough to enable the same or close to the same, results.
However, the above method has limitations. First, the choice of excitation must be such that a measurement interval (observation time slot) contains an integer number of periods of all the signals to be measured. Also, some samples (as the first samples for different but still close frequencies) must be taken closer in time than the time interval required by analog-to-digital converters (ADC) to perform each conversion. One workaround to the problem would be using several ADCs in parallel, but it will result in increased cost and excessive complexity.
Further complications arise when multiple channels should be digitized simultaneously, as it is typical when mapping of the 3D distribution of impedance variations. For n excitation sine waves and m measurement inputs the number of ADC's would be m times n, which is clearly not feasible.
Therefore, there is a need for yet another alternative approach.